Global Observations of Geomagnetically Induced Currents Caused by an Extremely Intense Density Pulse During a Coronal Mass Ejection
Bibliographic record
Abstract
Abstract A variety of magnetosphere‐ionosphere current systems and waves have been linked to geomagnetic disturbance (GMD) and geomagnetically induced currents (GIC). However, since many location‐specific factors control GMD and GIC intensity, it is often unclear what mechanisms generate the largest GMD and GIC in different locations. We address this challenge through analysis of multi‐satellite measurements and globally distributed magnetometer and GIC measurements. We find embedded within the magnetic cloud of the 23–24 April 2023 coronal mass ejection (CME) storm there was a global scale density pulse lasting for 10–20 min with compression ratio of . It caused substantial dayside displacements of the bow shock and magnetopause, changes of and , respectively, which in turn caused large amplitude GMD in the magnetosphere and on the ground across a wide local time range. At the time this global GMD was observed, GIC measured in New Zealand, Finland, Canada, and the United States were observed. The GIC were comparable (within factors of 2–2.5) to the largest ever recorded during 14 year monitoring intervals in New Zealand and Finland and represented 2‐year maxima in the United States during a period with several Kp7 geomagnetic storms. Additionally, the GIC measurements in the USA and other mid‐latitude locations exhibited wave‐like fluctuations with 1–2 min period. This work suggests that large density pulses in CME should be considered an important driver of large amplitude, global GMD and among the largest GIC at mid‐latitude locations, and that sampling intervals are required to capture these GMD/GIC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".